Text Mining in Big Data Analytics

被引:123
|
作者
Hassani, Hossein [1 ]
Beneki, Christina [2 ]
Unger, Stephan [3 ]
Mazinani, Maedeh Taj [4 ]
Yeganegi, Mohammad Reza [5 ]
机构
[1] Univ Tehran, Res Inst Energy Management & Planning, Tehran 1417466191, Iran
[2] Ionian Univ, Fac Econ Sci, Dept Tourism, Kalypso Bldg,4 P Vraila Armeni, Corfu 49100, Greece
[3] St Anselm Coll, Dept Econ & Business, 100 St Anselm Drive, Manchester, NH 03103 USA
[4] Univ Tehran, Dept Management, Tehran 1417466191, Iran
[5] Islamic Azad Univ, Cent Tehran Branch, Dept Accounting, Tehran 1955847781, Iran
关键词
text mining; big data; analytics; review; WEB SERVER LOGS; SOCIAL-MEDIA; SENTIMENT ANALYSIS; INFORMATION EXTRACTION; KEYWORD EXTRACTION; USER NAVIGATION; CHILD-ABUSE; FAKE NEWS; FRAMEWORK; BLOG;
D O I
10.3390/bdcc4010001
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Text mining in big data analytics is emerging as a powerful tool for harnessing the power of unstructured textual data by analyzing it to extract new knowledge and to identify significant patterns and correlations hidden in the data. This study seeks to determine the state of text mining research by examining the developments within published literature over past years and provide valuable insights for practitioners and researchers on the predominant trends, methods, and applications of text mining research. In accordance with this, more than 200 academic journal articles on the subject are included and discussed in this review; the state-of-the-art text mining approaches and techniques used for analyzing transcripts and speeches, meeting transcripts, and academic journal articles, as well as websites, emails, blogs, and social media platforms, across a broad range of application areas are also investigated. Additionally, the benefits and challenges related to text mining are also briefly outlined.
引用
收藏
页码:1 / 34
页数:34
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